UID:
almahu_9948613607102882
Format:
XIV, 245 p. 117 illus.
,
online resource.
Edition:
1st ed. 2021.
ISBN:
9783030580551
Series Statement:
Progress in Geophysics,
Content:
This book gives the reader the basic knowledge of the theory of random processes necessary for applying to study climatic time series. It contains many examples in different areas of time series analysis such as autoregressive modelling and spectral analysis, linear extrapolation, simulation, causality, relations between scalar components of multivariate time series, and reconstructions of climate data. As an important feature, the book contains many practical examples and recommendations about how to deal and how not to deal with applied problems of time series analysis in climatology or any other science where the time series are short.
Note:
Chapter 1 - Introduction -- Chapter 2 - Basics of Scalar Random Processes -- Chapter 3 - Time and Frequency Domain Models of Scalar Time Series -- Chapter 4 - Practical Analysis of Time Series.-Chapter 5 - Stochastic models and spectra of climatic and related time series -- Chapter 6 - Statistical Forecasting of Geophysical Processes -- Chapter 7 - Bivariate Time Series Analysis -- Chapter 8 - Teleconnection Research and Bivariate Extrapolation -- Chapter 9 - Reconstruction of Time Series -- Chapter 10 - Frequency domain structure and feedbacks in QBO time series -- Chapter 11- Verification of General Circulation Models -- Chapter 12 - Applications to proxy data -- Chapter 13 - Application to Sunspot Numbers and Total Solar Irradiance -- Chapter 14 - Multivariate time and frequency domain analysis -- Chapter 15 - Summary and Recommendations.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030580544
Additional Edition:
Printed edition: ISBN 9783030580568
Language:
English
DOI:
10.1007/978-3-030-58055-1
URL:
https://doi.org/10.1007/978-3-030-58055-1
